Metadata compaction

ABSTRACT

Techniques are provided for compacting indirect blocks. For example, an object is represented as a structure comprising data blocks within which data of the object is stored and indirect blocks comprising block numbers of where the data blocks are located in storage. Block numbers within a set of indirect blocks are compacted into a compacted indirect block comprising a base block number, a count of additional block numbers after the base block number in the compacted indirect block, and a pattern of the block numbers in the compacted indirect block. The compacted indirect block is stored into memory for processing access operations to the object. Storing compacted indirect blocks into memory allows for more block numbers to be stored within memory. This improves the processing of access operations because reading the block numbers from memory is faster than loading the block numbers from disk.

RELATED APPLICATION

This application claims priority to and is a continuation of U.S. patentapplication Ser. No. 17,083,945, titled “METADATA COMPACTION” and filedon Oct. 29, 2020, which claims priority to and is a continuation of U.S.Pat. No. 10,852,994, titled “METADATA COMPACTION” and filed on Mar. 27,2019, which are incorporated herein by reference.

BACKGROUND

A volume is a storage area within a file system. The file system mayallow users to create and store objects within the volume, such asfiles, directories, or other storage objects. The file system may storedata of objects into data blocks of storage devices. That is, the filesystem divides the storage capacity of storage devices into data blockshaving a particular size, such as 4096 bytes or any other size. Thephysical location of each data block within a storage device isaddressable by a block number, such as a physical block number orvirtual block number.

An object may be represented as a structure by the file system. Forexample, a file may be represented by a hierarchical tree structure. Thehierarchical tree structure comprises leaf nodes that are the datablocks within which user data is stored. The hierarchical tree structurecomprises one or more levels of intermediate nodes that are indirectblocks comprising block numbers (pointers) used to address/locate blocksof a lower level of the hierarchical tree structure. For example, theleaf nodes are at a level (0). Intermediate nodes at a level (1)comprise block numbers pointing to data blocks of the leaf nodes.Intermediate nodes at a level (2) comprise block numbers pointing to theintermediate nodes at the level (1). In this way, the hierarchical treestructure may be traversed to locate and access user data at particularphysical locations within storage based upon block numbers withinintermediate nodes.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a component block diagram illustrating an example clusterednetwork in which an embodiment of the invention may be implemented.

FIG. 2 is a component block diagram illustrating an example data storagesystem in which an embodiment of the invention may be implemented.

FIG. 3 is a flow chart illustrating an example method for indirect blockcompaction.

FIG. 4A is a component block diagram illustrating an example system forindirect block compaction.

FIG. 4B is a component block diagram illustrating an example system forindirect block compaction, where indirect blocks are compacted andpacked into a compacted indirect block.

FIG. 5 is an example of a computer readable medium in which anembodiment of the invention may be implemented.

FIG. 6 is a component block diagram illustrating an example computingenvironment in which an embodiment of the invention may be implemented.

DETAILED DESCRIPTION

Some examples of the claimed subject matter are now described withreference to the drawings, where like reference numerals are generallyused to refer to like elements throughout. In the following description,for purposes of explanation, numerous specific details are set forth inorder to provide an understanding of the claimed subject matter. It maybe evident, however, that the claimed subject matter may be practicedwithout these specific details. Nothing in this detailed description isadmitted as prior art.

A computing device, such as a storage controller, a computing node of acluster, a computer, a storage virtual machine, a storage service, etc.,may implement a file system that allows users to store data within avolume. The file system may represent an object, such as a file, of thevolume using a structure comprising data blocks within which data of theobject are stored and indirect blocks comprising block numbers of wherethe data blocks or other indirect blocks are located in storage. Whendata of the object is requested by an access operation (e.g., a read orwrite operation), the structure is use to identify the location ofcorresponding data blocks within storage.

The file system may store the data blocks and indirect blocks withinstorage and/or memory of the computing device. The blocks may be storedaccording to a block size used by the file system, such as 4096 bytes orany other size. Storing blocks within memory, such as by caching userdata, allows the computing device to process access operations targetingthe blocks faster than if the data is read from storage (e.g., a harddisk device, cloud storage, a solid state storage device, or otherstorage device may have higher latency than the memory). The size ofmemory may be limited compared to the size of a storage device, and thusonly so much data can be stored within memory. Because the indirectblocks are used to identify the data blocks for processing accessoperations, it would be advantageous to store as many indirect blockscontaining block numbers as possible within memory to improve thelatency of processing access operations since reading indirect blocksfrom memory is faster than loading the indirect blocks from storage. Forexample, the ability to store more indirect blocks containing blocknumbers within memory will improve the processing time of random accessoperations that are larger than the block size used by the file systembecause less load operations of indirect blocks from storage areperformed.

Accordingly, as provided herein, indirect blocks are compacted to reducethe size of the indirect blocks so that multiple indirect blocks can bepacked into a single compacted indirect block having the same size as anindirect block. That is, the size of an indirect block may be 4096 bytesor any other block size used by a file system. Block numbers may be 6bytes or some other size, and thus only so many block numbers can bestored within an indirect block. The present system using an encodingscheme that compact the indirect block so that the same number of blocknumbers can be represented using less storage space. In this way,multiple indirect blocks can be stored into a single compacted indirectblock representing all of the block numbers of those indirect blocksusing the same 4096 bytes. As will be subsequently described in furtherdetail, block numbers are compacted (encoding) using the encoding schemebased upon various patterns of block numbers, such as sequential blocknumbers, repeating block numbers, or offsets between block numbers. Itmay be appreciated that other compression techniques beyondcompaction/encoding are contemplated, and that any type of data and/ormetadata may be compressed, compacted, encoded, etc. so that more dataand/or metadata may be stored (e.g., cached) in memory as opposed tohaving to be read from disk.

Compacting indirect blocks so that more block numbers can be representedusing the same amount of storage space allows for more indirect blocksand thus block numbers to be stored within memory. Because more indirectblocks containing block numbers are stored within memory, the latency ofprocessing access operations is improved. This is because there is ahigher likelihood that block numbers used to locate request data blockstargeted by access operations will be in memory instead of storage wherea disk read operation would have to be performed. In this way, moreindirect blocks can be stored within memory. Because more indirectblocks can be represented using less storage space, there is storagesavings for storing indirect blocks as compacted indirect blocks. Also,when processing random access operations (e.g., a read operation tonon-sequential block numbers), there may be less load operations ofindirect blocks from storage due to more indirect blocks being storedwithin memory. For example, one disk read can be saved. Compactingindirect blocks also provides for path length reduction in a storagelayer due to less indirect blocks being flushed from memory to storage.Further, because a block number can be selectively read from a compactedindirect block without having to uncompact the entire compacted indirectblock, processor resources otherwise wasted in uncompacting the entirecompacted indirect block are conserved.

It may be appreciated that a variety of different data and/or metadatacan be compacted. For example, metadata (e.g., a size of a volume, amodification date of a file, a creation time of a file, a name of anaggregate, and/or a variety of other information relating to volumes,aggregates, files, a state of a replication relationship, and/or otherdata relating to the operation of storage services and a storageoperating system) may be compacted to create compacted metadata. Thecompacted metadata may be stored within memory for efficient access.

To provide for indirect block compaction, FIG. 1 illustrates anembodiment of a clustered network environment 100 or a network storageenvironment. It may be appreciated, however, that the techniques, etc.described herein may be implemented within the clustered networkenvironment 100, a non-cluster network environment, and/or a variety ofother computing environments, such as a desktop computing environment.That is, the instant disclosure, including the scope of the appendedclaims, is not meant to be limited to the examples provided herein. Itwill be appreciated that where the same or similar components, elements,features, items, modules, etc. are illustrated in later figures but werepreviously discussed with regard to prior figures, that a similar (e.g.,redundant) discussion of the same may be omitted when describing thesubsequent figures (e.g., for purposes of simplicity and ease ofunderstanding).

FIG. 1 is a block diagram illustrating the clustered network environment100 that may implement at least some embodiments of the techniquesand/or systems described herein. The clustered network environment 100comprises data storage systems 102 and 104 that are coupled over acluster fabric 106, such as a computing network embodied as a privateInfiniband, Fibre Channel (FC), or Ethernet network facilitatingcommunication between the data storage systems 102 and 104 (and one ormore modules, component, etc. therein, such as, computing nodes 116 and118, for example). It will be appreciated that while two data storagesystems 102 and 104 and two computing nodes 116 and 118 are illustratedin FIG. 1 , that any suitable number of such components is contemplated.In an example, computing nodes 116, 118 comprise storage controllers(e.g., computing node 116 may comprise a primary or local storagecontroller and computing node 118 may comprise a secondary or remotestorage controller) that provide client devices, such as host devices108, 110, with access to data stored within data storage devices 128,130. Similarly, unless specifically provided otherwise herein, the sameis true for other modules, elements, features, items, etc. referencedherein and/or illustrated in the accompanying drawings. That is, aparticular number of components, modules, elements, features, items,etc. disclosed herein is not meant to be interpreted in a limitingmanner.

It will be further appreciated that clustered networks are not limitedto any particular geographic areas and can be clustered locally and/orremotely. Thus, in an embodiment a clustered network can be distributedover a plurality of storage systems and/or computing nodes located in aplurality of geographic locations; while In an embodiment a clusterednetwork can include data storage systems (e.g., 102, 104) residing in asame geographic location (e.g., in a single onsite rack of data storagedevices).

In the illustrated example, one or more host devices 108, 110 which maycomprise, for example, client devices, personal computers (PCs),computing devices used for storage (e.g., storage servers), and othercomputers or peripheral devices (e.g., printers), are coupled to therespective data storage systems 102, 104 by storage network connections112, 114. Network connection may comprise a local area network (LAN) orwide area network (WAN), for example, that utilizes Network AttachedStorage (NAS) protocols, such as a Common Internet File System (CIFS)protocol or a Network File System (NFS) protocol to exchange datapackets, a Storage Area Network (SAN) protocol, such as Small ComputerSystem Interface (SCSI) or Fiber Channel Protocol (FCP), an objectprotocol, such as S3, etc. Illustratively, the host devices 108, 110 maybe general-purpose computers running applications, and may interact withthe data storage systems 102, 104 using a client/server model forexchange of information. That is, the host device may request data fromthe data storage system (e.g., data on a storage device managed by anetwork storage control configured to process I/O commands issued by thehost device for the storage device), and the data storage system mayreturn results of the request to the host device via one or more storagenetwork connections 112, 114.

The computing nodes 116, 118 on clustered data storage systems 102, 104can comprise network or host nodes that are interconnected as a clusterto provide data storage and management services, such as to anenterprise having remote locations, cloud storage (e.g., a storageendpoint may be stored within a data cloud), etc., for example. Such acomputing node in the clustered network environment 100 can be a deviceattached to the network as a connection point, redistribution point orcommunication endpoint, for example. A computing node may be capable ofsending, receiving, and/or forwarding information over a networkcommunications channel, and could comprise any device that meets any orall of these criteria. One example of a computing node may be a datastorage and management server attached to a network, where the servercan comprise a general purpose computer or a computing deviceparticularly configured to operate as a server in a data storage andmanagement system.

In an example, a first cluster of computing nodes such as the computingnodes 116, 118 (e.g., a first set of storage controllers configured toprovide access to a first storage aggregate comprising a first logicalgrouping of one or more storage devices) may be located on a firststorage site. A second cluster of computing nodes, not illustrated, maybe located at a second storage site (e.g., a second set of storagecontrollers configured to provide access to a second storage aggregatecomprising a second logical grouping of one or more storage devices).The first cluster of computing nodes and the second cluster of computingnodes may be configured according to a disaster recovery configurationwhere a surviving cluster of computing nodes provides switchover accessto storage devices of a disaster cluster of computing nodes in the eventa disaster occurs at a disaster storage site comprising the disastercluster of computing nodes (e.g., the first cluster of computing nodesprovides client devices with switchover data access to storage devicesof the second storage aggregate in the event a disaster occurs at thesecond storage site).

As illustrated in the clustered network environment 100, computing nodes116, 118 can comprise various functional components that coordinate toprovide distributed storage architecture for the cluster. For example,the computing nodes can comprise network modules 120, 122 and diskmodules 124, 126. Network modules 120, 122 can be configured to allowthe computing nodes 116, 118 (e.g., network storage controllers) toconnect with host devices 108, 110 over the storage network connections112, 114, for example, allowing the host devices 108, 110 to access datastored in the distributed storage system. Further, the network modules120, 122 can provide connections with one or more other componentsthrough the cluster fabric 106. For example, in FIG. 1 , the networkmodule 120 of computing node 116 can access a second data storage deviceby sending a request through the disk module 126 of computing node 118.

Disk modules 124, 126 can be configured to connect one or more datastorage devices 128, 130, such as disks or arrays of disks, flashmemory, or some other form of data storage, to the computing nodes 116,118. The computing nodes 116, 118 can be interconnected by the clusterfabric 106, for example, allowing respective computing nodes in thecluster to access data on data storage devices 128, 130 connected todifferent computing nodes in the cluster. Often, disk modules 124, 126communicate with the data storage devices 128, 130 according to the SANprotocol, such as SCSI or FCP, for example. Thus, as seen from anoperating system on computing nodes 116, 118, the data storage devices128, 130 can appear as locally attached to the operating system. In thismanner, different computing nodes 116, 118, etc. may access data blocksthrough the operating system, rather than expressly requesting abstractfiles.

It should be appreciated that, while the clustered network environment100 illustrates an equal number of network and disk modules, otherembodiments may comprise a differing number of these modules. Forexample, there may be a plurality of network and disk modulesinterconnected in a cluster that does not have a one-to-onecorrespondence between the network and disk modules. That is, differentcomputing nodes can have a different number of network and disk modules,and the same computing node can have a different number of networkmodules than disk modules.

Further, a host device 108, 110 can be networked with the computingnodes 116, 118 in the cluster, over the storage networking connections112, 114. As an example, respective host devices 108, 110 that arenetworked to a cluster may request services (e.g., exchanging ofinformation in the form of data packets) of computing nodes 116, 118 inthe cluster, and the computing nodes 116, 118 can return results of therequested services to the host devices 108, 110. In an embodiment, thehost devices 108, 110 can exchange information with the network modules120, 122 residing in the computing nodes 116, 118 (e.g., network hosts)in the data storage systems 102, 104.

In an embodiment, the data storage devices 128, 130 comprise volumes132, which is an implementation of storage of information onto diskdrives or disk arrays or other storage (e.g., flash) as a file-systemfor data, for example. In an example, a disk array can include alltraditional hard drives, all flash drives, or a combination oftraditional hard drives and flash drives. Volumes can span a portion ofa disk, a collection of disks, or portions of disks, for example, andtypically define an overall logical arrangement of file storage on diskspace in the storage system. In an embodiment a volume can comprisestored data as one or more files that reside in a hierarchical directorystructure within the volume.

Volumes are typically configured in formats that may be associated withparticular storage systems, and respective volume formats typicallycomprise features that provide functionality to the volumes, such asproviding an ability for volumes to form clusters. For example, where afirst storage system may utilize a first format for their volumes, asecond storage system may utilize a second format for their volumes.

In the clustered network environment 100, the host devices 108, 110 canutilize the data storage systems 102, 104 to store and retrieve datafrom the volumes 132. In this embodiment, for example, the host device108 can send data packets to the network module 120 in the computingnode 116 within data storage system 102. The computing node 116 canforward the data to the data storage device 128 using the disk module124, where the data storage device 128 comprises volume 132A. In thisway, in this example, the host device can access the volume 132A, tostore and/or retrieve data, using the data storage system 102 connectedby the storage network connection 112. Further, in this embodiment, thehost device 110 can exchange data with the network module 122 in thecomputing node 118 within the data storage system 104 (e.g., which maybe remote from the data storage system 102). The computing node 118 canforward the data to the data storage device 130 using the disk module126, thereby accessing volume 1328 associated with the data storagedevice 130.

It may be appreciated that indirect block compaction may be implementedwithin the clustered network environment 100. It may be appreciated thatindirect block compaction may be implemented for and/or between any typeof computing environment, and may be transferrable between physicaldevices (e.g., computing node 116, computing node 118, a desktopcomputer, a tablet, a laptop, a wearable device, a mobile device, astorage device, a server, etc.) and/or a cloud computing environment(e.g., remote to the clustered network environment 100).

FIG. 2 is an illustrative example of a data storage system 200 (e.g.,102, 104 in FIG. 1 ), providing further detail of an embodiment ofcomponents that may implement one or more of the techniques and/orsystems described herein. The data storage system 200 comprises acomputing node 202 (e.g., computing nodes 116, 118 in FIG. 1 ), and adata storage device 234 (e.g., data storage devices 128, 130 in FIG. 1). The computing node 202 may be a general purpose computer, forexample, or some other computing device particularly configured tooperate as a storage server. A host device 205 (e.g., 108, 110 in FIG. 1) can be connected to the computing node 202 over a network 216, forexample, to provide access to files and/or other data stored on the datastorage device 234. In an example, the computing node 202 comprises astorage controller that provides client devices, such as the host device205, with access to data stored within data storage device 234.

The data storage device 234 can comprise mass storage devices, such asdisks 224, 226, 228 of a disk array 218, 220, 222. It will beappreciated that the techniques and systems, described herein, are notlimited by the example embodiment. For example, disks 224, 226, 228 maycomprise any type of mass storage devices, including but not limited tomagnetic disk drives, flash memory, and any other similar media adaptedto store information, including, for example, data (D) and/or parity (P)information.

The computing node 202 comprises one or more processors 204, a memory206, a network adapter 210, a cluster access adapter 212, and a storageadapter 214 interconnected by a system bus 242. The data storage system200 also includes an operating system 208 installed in the memory 206 ofthe computing node 202 that can, for example, implement a RedundantArray of Independent (or Inexpensive) Disks (RAID) optimizationtechnique to optimize a reconstruction process of data of a failed diskin an array.

The operating system 208 can also manage communications for the datastorage system, and communications between other data storage systemsthat may be in a clustered network, such as attached to a cluster fabric215 (e.g., 106 in FIG. 1 ). Thus, the computing node 202, such as anetwork storage controller, can respond to host device requests tomanage data on the data storage device 234 (e.g., or additionalclustered devices) in accordance with these host device requests. Theoperating system 208 can often establish one or more file systems on thedata storage system 200, where a file system can include software codeand data structures that implement a persistent hierarchical namespaceof files and directories, for example. As an example, when a new datastorage device (not shown) is added to a clustered network system, theoperating system 208 is informed where, in an existing directory tree,new files associated with the new data storage device are to be stored.This is often referred to as “mounting” a file system.

In the example data storage system 200, memory 206 can include storagelocations that are addressable by the processors 204 and adapters 210,212, 214 for storing related software application code and datastructures. The processors 204 and adapters 210, 212, 214 may, forexample, include processing elements and/or logic circuitry configuredto execute the software code and manipulate the data structures. Theoperating system 208, portions of which are typically resident in thememory 206 and executed by the processing elements, functionallyorganizes the storage system by, among other things, invoking storageoperations in support of a file service implemented by the storagesystem. It will be apparent to those skilled in the art that otherprocessing and memory mechanisms, including various computer readablemedia, may be used for storing and/or executing application instructionspertaining to the techniques described herein. For example, theoperating system can also utilize one or more control files (not shown)to aid in the provisioning of virtual machines.

The network adapter 210 includes the mechanical, electrical andsignaling circuitry needed to connect the data storage system 200 to ahost device 205 over a network 216, which may comprise, among otherthings, a point-to-point connection or a shared medium, such as a localarea network. The host device 205 (e.g., 108, 110 of FIG. 1 ) may be ageneral-purpose computer configured to execute applications. Asdescribed above, the host device 205 may interact with the data storagesystem 200 in accordance with a client/host model of informationdelivery.

The storage adapter 214 cooperates with the operating system 208executing on the computing node 202 to access information requested bythe host device 205 (e.g., access data on a storage device managed by anetwork storage controller). The information may be stored on any typeof attached array of writeable media such as magnetic disk drives, flashmemory, and/or any other similar media adapted to store information. Inthe example data storage system 200, the information can be stored indata blocks on the disks 224, 226, 228. The storage adapter 214 caninclude input/output (I/O) interface circuitry that couples to the disksover an I/O interconnect arrangement, such as a storage area network(SAN) protocol (e.g., Small Computer System Interface (SCSI), iSCSI,hyperSCSI, Fiber Channel Protocol (FCP)). The information is retrievedby the storage adapter 214 and, if necessary, processed by the one ormore processors 204 (or the storage adapter 214 itself) prior to beingforwarded over the system bus 242 to the network adapter 210 (and/or thecluster access adapter 212 if sending to another computing node in thecluster) where the information is formatted into a data packet andreturned to the host device 205 over the network 216 (and/or returned toanother computing node attached to the cluster over the cluster fabric215).

In an embodiment, storage of information on disk arrays 218, 220, 222can be implemented as one or more storage volumes 230, 232 that arecomprised of a cluster of disks 224, 226, 228 defining an overalllogical arrangement of disk space. The disks 224, 226, 228 that compriseone or more volumes are typically organized as one or more groups ofRAIDs. As an example, volume 230 comprises an aggregate of disk arrays218 and 220, which comprise the cluster of disks 224 and 226.

In an embodiment, to facilitate access to disks 224, 226, 228, theoperating system 208 may implement a file system (e.g., write anywherefile system) that logically organizes the information as a hierarchicalstructure of directories and files on the disks. In this embodiment,respective files may be implemented as a set of disk blocks configuredto store information, whereas directories may be implemented asspecially formatted files in which information about other files anddirectories are stored.

Whatever the underlying physical configuration within this data storagesystem 200, data can be stored as files within physical and/or virtualvolumes, which can be associated with respective volume identifiers,such as file system identifiers (FSIDs), which can be 32-bits in lengthin one example.

A physical volume corresponds to at least a portion of physical storagedevices whose address, addressable space, location, etc. doesn't change,such as at least some of one or more data storage devices 234 (e.g., aRedundant Array of Independent (or Inexpensive) Disks (RAID system)).Typically the location of the physical volume doesn't change in that the(range of) address(es) used to access it generally remains constant.

A virtual volume, in contrast, is stored over an aggregate of disparateportions of different physical storage devices. The virtual volume maybe a collection of different available portions of different physicalstorage device locations, such as some available space from each of thedisks 224, 226, and/or 228. It will be appreciated that since a virtualvolume is not “tied” to any one particular storage device, a virtualvolume can be said to include a layer of abstraction or virtualization,which allows it to be resized and/or flexible in some regards.

Further, a virtual volume can include one or more logical unit numbers(LUNs) 238, directories 236, Qtrees 235, and files 240. Among otherthings, these features, but more particularly LUNS, allow the disparatememory locations within which data is stored to be identified, forexample, and grouped as data storage unit. As such, the LUNs 238 may becharacterized as constituting a virtual disk or drive upon which datawithin the virtual volume is stored within the aggregate. For example,LUNs are often referred to as virtual drives, such that they emulate ahard drive from a general purpose computer, while they actually comprisedata blocks stored in various parts of a volume.

In an embodiment, one or more data storage devices 234 can have one ormore physical ports, wherein each physical port can be assigned a targetaddress (e.g., SCSI target address). To represent respective volumesstored on a data storage device, a target address on the data storagedevice can be used to identify one or more LUNs 238. Thus, for example,when the computing node 202 connects to a volume 230, 232 through thestorage adapter 214, a connection between the computing node 202 and theone or more LUNs 238 underlying the volume is created.

In an embodiment, respective target addresses can identify multipleLUNs, such that a target address can represent multiple volumes. The I/Ointerface, which can be implemented as circuitry and/or software in thestorage adapter 214 or as executable code residing in memory 206 andexecuted by the processors 204, for example, can connect to volume 230by using one or more addresses that identify the one or more LUNs 238.

It may be appreciated that indirect block compaction may be implementedfor the data storage system 200. It may be appreciated that indirectblock compaction may be implemented for and/or between any type ofcomputing environment, and may be transferrable between physical devices(e.g., computing node 202, host device 205, a desktop computer, atablet, a laptop, a wearable device, a mobile device, a storage device,a server, etc.) and/or a cloud computing environment (e.g., remote tothe computing node 202 and/or the host device 205).

One embodiment of indirect block compaction is illustrated by anexemplary method 300 of FIG. 3 and further described in conjunction withsystem 400 of FIGS. 4A-4B. A computing device 402 (e.g., a computingnode, a storage controller, a computer, a storage virtual machine,software or hardware or combination thereof, etc.) may comprise and/orutilize memory 404 and/or other computing resources. The computingdevice 402 may have access to storage 406, such as a hard disk drive, asolid state storage device, attached storage, network attached storage,cloud storage, etc. The memory 404 may provide the computing device 402with faster read and write times than the storage 406, but the amount ofstorage space in memory 404 may be limited compared to the storage 406.Thus, the computing device 402 may cache certain data within memory 404for faster access in order to process access operations, such as readand write operations, faster than if data has to be loaded from thestorage 406.

At 302, a file system of the computing device 402 may represent anobject, such as a file, as a structure 408 such as a hierarchical treestructure of nodes representing user data in leaf nodes (e.g., datablocks of user data) and intermediates nodes of indirect blockscomprising block numbers (e.g., pointers or addresses) of other nodes(e.g., a level (2) intermediate node may comprise block numbers of oneor more level (1) intermediate nodes, a level (1) intermediate node maycomprise block numbers of one or more level (0) leaf nodes, etc.). Thestructure 408 may comprise any number of levels of nodes.

In an example, the structure 408 comprise a root node 410, such as aninode of the file. The structure 408 may comprise a level (1) ofintermediate nodes, such as a first indirect block 412, a secondindirect block 414, and/or other indirect blocks not illustrated. Thestructure 408 may comprise a level (0) of leaf nodes, such as a datablock (A) 416 of user data of the object, a data block (B) 418 of userdata of the object, a data block (C) 420 of user data of the object,etc. Each indirect block and data block may have a block size used bythe file system to store data, such as 4096 bytes. Each indirect blockand data block may be assigned a block number used to locate/addresseach indirect block and data block. The data blocks comprise user data,and the indirect blocks comprise block numbers of other blocks. Forexample, the first indirect block 412 comprises block numbers of thedata block (A) 416, the data block (B) 418, and/or other data blocks notillustrated. The second indirect block 414 comprises block numbers ofthe data block (C) 420 and/or other data blocks not illustrated. Theroot node 410 may comprise block numbers of the first indirect block412, the second indirect block 414, and/or other indirect blocks. It maybe appreciated that the structure 408 illustrated in FIG. 4A is merely asimplistic example of a structure, and that structures may comprise morenodes, levels of nodes, and/or types of nodes and data.

When an access operation is received to access user data within the datablocks (leaf nodes), the structure 408 is traversed to locate such datablocks. For example, the root node 410 may be traversed to identify thefirst indirect block 412 as comprising a block number for the data block(B) 418 that is to be read by a read operation. Thus, the first indirectblock 412 is traversed to obtain the block number that is then used toaccess the data block (B) 418 since the block number corresponds to alocation/address of the data block (B) 418 (e.g., a physical location ofthe data block (B) 418 within the storage 406).

Because the structure 408 is traversed and used for locating datatargeted by access operations, it is advantageous to store as manyindirect blocks of the structure 408 in the lower latency memory 404 aspossible because accessing indirect blocks from the memory 404 is muchfaster than having to load the indirect blocks from storage 406, thusimproving latency. However, the amount of data that can be stored withinthe memory 404 may be significantly less than the amount of data thatcan be stored in the storage 406. Accordingly, as provided herein,indirect blocks are compacted to reduce their size so that multipleindirect blocks can be packed into a single compacted indirect blockthat is the same size of a single indirect block, but is capable ofrepresenting more block numbers than a single indirect block. Becausemultiple indirect blocks are packed into a single compacted indirectblock, the compacted indirect block will now store more block numbersthan a single indirect block. In this way, more block numbers can bestored within memory 404 using the same memory footprint because eachcompacted indirect block has the same size as a single indirect block,but also has more block numbers than the single indirect block becausemultiple indirect blocks are packed into the compacted indirect block.

At 304, one or more indirect blocks, such as the first indirect block412, the second indirect block 414, a third indirect block 430, and/orother indirect blocks are compacted 432 and packed into a compactedindirect block 434, as illustrated by FIG. 4B. In an example ofcompacting 432 the first indirect block 412, block numbers within thefirst indirect block 412 are compacted (encoded) using the encodingscheme that is based upon patterns of the block numbers, such as whetherblock numbers are sequential (e.g., a sequential pattern of blocknumbers 50, 51, 52, and 53), repeating (e.g., a repeating pattern ofblock numbers 60, 60, and 60), or offsets from a base block number(e.g., a base block number of 50 along with other block numbers 55 and70 that are offset from the base block number of 50 by 5 and 20respectively). For a set of block numbers encoded within the compactedindirect block 434, there is a base block number, a count of subsequentblock numbers after the base block number, and a pattern of the set ofblock numbers. It may be appreciated that other compression techniquesbeyond compaction/encoding are contemplated, and that encoding basedupon length, offset, and pattern is merely one embodiment of how anytype of data and/or metadata may be compressed/compacted. Also, any typeof data and/or metadata may be compressed, compacted, encoded, etc. sothat more data and/or metadata may be stored (e.g., cached) in memory asopposed to having to be read from disk.

In an example, the first indirect block 412 comprises block numbers 357,358, 359, 360, 112, 112, 112, 370, 236, 375, and/or other block numbers.Because the first 4 block numbers are sequential, those block numbersare encoded as a base block number of 357, a count of 3 additionalsequential block numbers after the base block number of 357, and apattern of 1 corresponding to a sequential pattern. Thus, instead ofstoring 4 block numbers 357, 358, 359, and 360 that are 6 bytes each,merely a tuple is stored of (357, 3, 1). Because the next 3 blocknumbers are repeating, those block numbers are encoded as a base blocknumber of 112, a count of 2 additional repeating block numbers after thebase block number of 112, and a pattern of 2 corresponding to a repeatpattern. Thus, instead of storing 3 block numbers 112, 112, and 112 thatare 6 bytes each, merely a tuple is stored of (112, 2, 2). Because thelast 3 block numbers may be close enough to a base block number, thoseblock numbers are encoded as a base block number of 370, a count of 2additional block numbers after the base block number of 370, a patternof 3 corresponding to an offset pattern, and offsets −134 and 5 of theadditional block numbers being offset from the base block number of 370.Thus, instead of storing 3 block numbers 370, 236, and 375 that are 6bytes each, merely (370, 2, 3, −134, 5) is stored. Storing (370, 2, 3,−134, 5) saves storage space compared to storing the 3 block numbersbecause the length, offset, and pattern can be stored using just a fewbits, which is less than the amount of bits otherwise used to store the3 block numbers.

In this way, the size of the indirect blocks is significantly reduced bycompaction 432 and encoding of block numbers. This allows for multipleindirect blocks and the encoded block numbers to be packed into thesingle compacted indirect block 434 that can now represent more blocknumbers than a single indirect block using the same block size ofinformation such as 4096 bytes.

Other information may be represented within the compacted indirect block434. For example, data blocks may be compressed into compression groups.In an example, a compression group corresponds to a relatively smallgroup of consecutive blocks that are compressed together. For example, afile is divided into chunks of data referred to as compression groups.Each compression group may have a size limit, such as 32 kb or any othersize. Each compression group comprises data from only a single file.Compression may be limited to files having a certain minimum size suchas 8 bk or larger. Using a compression group can improve I/O, such aswhere a read operation for compressed data only reads the compressiongroups that contain the requested data instead of an entire file. If ablock number within the compacted indirect block 434 corresponds to adata block within a compression group, then a compression groupindicator is added into the compacted indirect block 434 for the blocknumber.

Block numbers of the indirect blocks being compacted 432 are encodedinto compaction groups. The number of blocks that can be encoded into acompaction group may be limited to a threshold amount, such as 32 blocknumbers. Offsets of each compaction group within the compacted indirectblock 434 are stored within a header of the compacted indirect block434. In an example, a lookup table is created for the compacted indirectblock 434. The lookup table is used to identify offsets of compactiongroups within the compacted indirect block 434 of the object.

In this way, multiple indirect blocks are compacted to smaller sizes byencoding block numbers to create a compacted indirect block 434representing more block numbers than a single indirect block but byusing the same storage space (block size) as an uncompacted indirectblock. Further, more block numbers can be stored within the memory 404of the computer device 402. For example, the memory 404 may have spaceto store ten 4096 byte indirect blocks that each comprise 50 blocknumbers. Normally, only 500 block numbers would be represented by the 10indirect blocks stored into the memory 404. However, since compactedindirect blocks may be capable of representing 200 block numbers usingthe same 4096 bytes, 2,000 block numbers would be represented by 10compacted indirect blocks stored in the memory 404. It may beappreciated that these numbers are merely used for illustrative purposesand simplicity. Accordingly, the compacted indirect block 434 and/orother compacted indirect blocks can be loaded into the memory 404, at306, so that the compacted indirect blocks can be accessed more quicklyand with lower latency for processing access operations (read and writeoperations) than if indirect blocks had to be loaded from the storage406.

In an example, a read request (read operation) for the data block (B)418 of the object is received by the computing device 402. A header ofthe compacted indirect block 434 is evaluated to identify an offset of acompaction group, within the compacted indirect block 434, comprising ablock number of the data block (B) 418. The block number is uncompactedfrom the compacted indirect block 434 to obtain the block number of thedata block (B) 418. To conserve processor resource utilization, othercompression groups are not uncompacted and thus the entire 4096 bytes ofthe compacted indirect block 434 does not need to be uncompacted. Theblock number is used to read the data block (B) 418 in order to processthe read request.

In an example, a write operation to write data to the object is receivedby the computing device 402. The write request may be executed to createdirty data (new data written by the write operation) marked to be storedto the storage 406 during a consistency point. During the consistencypoint, the dirty data is stored into the storage 406. Block numbers maybe assigned to data blocks into which the dirty data is stored. Thecompacted indirect block 434 may be uncompacted in order to identify allof the block numbers represented by the compacted indirect block 434.These block numbers along with the block numbers of the dirty data arethen recompacted to create one or more compacted indirect blocks. In anexample of performing the consistency point, block numbers are assignedto data blocks. The block numbers of the data blocks are then storedinto level (1) indirect blocks. Block numbers are then assigned to thelevel (1) indirect blocks. Any number of indirect block levels may becreated and assigned block numbers. Indirect blocks are then recompactedand packed into compacted indirect blocks. In an example, recompactionoccurs after block numbers of the data blocks are stored into the level(1) indirect blocks. In another example, recompaction occurs in parallelwith the storing of the block numbers into the level (1) indirectblocks.

It may be appreciated that a variety of different data and/or metadatacan be compacted. For example, metadata (e.g., a size of a volume, amodification date of a file, a creation time of a file, a name of anaggregate, and/or a variety of other information relating to volumes,aggregates, files, a state of a replication relationship, and/or otherdata relating to the operation of storage services and a storageoperating system) may be compacted to create compacted metadata. Thecompacted metadata may be stored within memory for efficient access.

Still another embodiment involves a computer-readable medium 500comprising processor-executable instructions configured to implement oneor more of the techniques presented herein. An example embodiment of acomputer-readable medium or a computer-readable device that is devisedin these ways is illustrated in FIG. 5 , wherein the implementationcomprises a computer-readable medium 508, such as a compactdisc-recordable (CD-R), a digital versatile disc-recordable (DVD-R),flash drive, a platter of a hard disk drive, etc., on which is encodedcomputer-readable data 506. This computer-readable data 506, such asbinary data comprising at least one of a zero or a one, in turncomprises a processor-executable computer instructions 504 configured tooperate according to one or more of the principles set forth herein. Insome embodiments, the processor-executable computer instructions 504 areconfigured to perform a method 502, such as at least some of theexemplary method 300 of FIG. 3 , for example. In some embodiments, theprocessor-executable computer instructions 504 are configured toimplement a system, such as at least some of the exemplary system 400 ofFIGS. 4A-4B, for example. Many such computer-readable media arecontemplated to operate in accordance with the techniques presentedherein.

FIG. 6 is a diagram illustrating an example operating environment 600 inwhich an embodiment of the techniques described herein may beimplemented. In one example, the techniques described herein may beimplemented within a client device 628, such as a laptop, tablet,personal computer, mobile device, wearable device, etc. In anotherexample, the techniques described herein may be implemented within astorage controller 630, such as a node configured to manage the storageand access to data on behalf of the client device 628 and/or otherclient devices. In another example, the techniques described herein maybe implemented within a distributed computing platform 602 such as acloud computing environment (e.g., a cloud storage environment, amulti-tenant platform, etc.) configured to manage the storage and accessto data on behalf of the client device 628 and/or other client devices.

In yet another example, at least some of the techniques described hereinare implemented across one or more of the client device 628, the storagecontroller 630, and the distributed computing platform 602. For example,the client device 628 may transmit operations, such as data operationsto read data and write data and metadata operations (e.g., a create fileoperation, a rename directory operation, a resize operation, a setattribute operation, etc.), over a network 626 to the storage controller630 for implementation by the storage controller 630 upon storage. Thestorage controller 630 may store data associated with the operationswithin volumes or other data objects/structures hosted within locallyattached storage, remote storage hosted by other computing devicesaccessible over the network 626, storage provided by the distributedcomputing platform 602, etc. The storage controller 630 may replicatethe data and/or the operations to other computing devices so that one ormore replicas, such as a destination storage volume that is maintainedas a replica of a source storage volume, are maintained. Such replicascan be used for disaster recovery and failover.

The storage controller 630 may store the data or a portion thereofwithin storage hosted by the distributed computing platform 602 bytransmitting the data to the distributed computing platform 602. In oneexample, the storage controller 630 may locally store frequentlyaccessed data within locally attached storage. Less frequently accesseddata may be transmitted to the distributed computing platform 602 forstorage within a data storage tier 608. The data storage tier 608 maystore data within a service data store 620, and may store clientspecific data within client data stores assigned to such clients such asa client (1) data store 622 used to store data of a client (1) and aclient (N) data store 624 used to store data of a client (N). The datastores may be physical storage devices or may be defined as logicalstorage, such as a virtual volume, LUNs, or other logical organizationsof data that can be defined across one or more physical storage devices.In another example, the storage controller 630 transmits and stores allclient data to the distributed computing platform 602. In yet anotherexample, the client device 628 transmits and stores the data directly tothe distributed computing platform 602 without the use of the storagecontroller 630.

The management of storage and access to data can be performed by one ormore storage virtual machines (SMVs) or other storage applications thatprovide software as a service (SaaS) such as storage software services.In one example, an SVM may be hosted within the client device 628,within the storage controller 630, or within the distributed computingplatform 602 such as by the application server tier 606. In anotherexample, one or more SVMs may be hosted across one or more of the clientdevice 628, the storage controller 630, and the distributed computingplatform 602.

In one example of the distributed computing platform 602, one or moreSVMs may be hosted by the application server tier 606. For example, aserver (1) 616 is configured to host SVMs used to execute applicationssuch as storage applications that manage the storage of data of theclient (1) within the client (1) data store 622. Thus, an SVM executingon the server (1) 616 may receive data and/or operations from the clientdevice 628 and/or the storage controller 630 over the network 626. TheSVM executes a storage application to process the operations and/orstore the data within the client (1) data store 622. The SVM maytransmit a response back to the client device 628 and/or the storagecontroller 630 over the network 626, such as a success message or anerror message. In this way, the application server tier 606 may hostSVMs, services, and/or other storage applications using the server (1)616, the server (N) 618, etc.

A user interface tier 604 of the distributed computing platform 602 mayprovide the client device 628 and/or the storage controller 630 withaccess to user interfaces associated with the storage and access of dataand/or other services provided by the distributed computing platform602. In an example, a service user interface 610 may be accessible fromthe distributed computing platform 602 for accessing services subscribedto by clients and/or storage controllers, such as data replicationservices, application hosting services, data security services, humanresource services, warehouse tracking services, accounting services,etc. For example, client user interfaces may be provided tocorresponding clients, such as a client (1) user interface 612, a client(N) user interface 614, etc. The client (1) can access various servicesand resources subscribed to by the client (1) through the client (1)user interface 612, such as access to a web service, a developmentenvironment, a human resource application, a warehouse trackingapplication, and/or other services and resources provided by theapplication server tier 606, which may use data stored within the datastorage tier 608.

The client device 628 and/or the storage controller 630 may subscribe tocertain types and amounts of services and resources provided by thedistributed computing platform 602. For example, the client device 628may establish a subscription to have access to three virtual machines, acertain amount of storage, a certain type/amount of data redundancy, acertain type/amount of data security, certain service level agreements(SLAs) and service level objectives (SLOs), latency guarantees,bandwidth guarantees, access to execute or host certain applications,etc. Similarly, the storage controller 630 can establish a subscriptionto have access to certain services and resources of the distributedcomputing platform 602.

As shown, a variety of clients, such as the client device 628 and thestorage controller 630, incorporating and/or incorporated into a varietyof computing devices may communicate with the distributed computingplatform 602 through one or more networks, such as the network 626. Forexample, a client may incorporate and/or be incorporated into a clientapplication (e.g., software) implemented at least in part by one or moreof the computing devices.

Examples of suitable computing devices include personal computers,server computers, desktop computers, nodes, storage servers, storagecontrollers, laptop computers, notebook computers, tablet computers orpersonal digital assistants (PDAs), smart phones, cell phones, andconsumer electronic devices incorporating one or more computing devicecomponents, such as one or more electronic processors, microprocessors,central processing units (CPU), or controllers. Examples of suitablenetworks include networks utilizing wired and/or wireless communicationtechnologies and networks operating in accordance with any suitablenetworking and/or communication protocol (e.g., the Internet). In usecases involving the delivery of customer support services, the computingdevices noted represent the endpoint of the customer support deliveryprocess, i.e., the consumer's device.

The distributed computing platform 602, such as a multi-tenant businessdata processing platform or cloud computing environment, may includemultiple processing tiers, including the user interface tier 604, theapplication server tier 606, and a data storage tier 608. The userinterface tier 604 may maintain multiple user interfaces, includinggraphical user interfaces and/or web-based interfaces. The userinterfaces may include the service user interface 610 for a service toprovide access to applications and data for a client (e.g., a “tenant”)of the service, as well as one or more user interfaces that have beenspecialized/customized in accordance with user specific requirements,which may be accessed via one or more APIs.

The service user interface 610 may include components enabling a tenantto administer the tenant's participation in the functions andcapabilities provided by the distributed computing platform 602, such asaccessing data, causing execution of specific data processingoperations, etc. Each processing tier may be implemented with a set ofcomputers, virtualized computing environments such as a storage virtualmachine or storage virtual server, and/or computer components includingcomputer servers and processors, and may perform various functions,methods, processes, or operations as determined by the execution of asoftware application or set of instructions.

The data storage tier 608 may include one or more data stores, which mayinclude the service data store 620 and one or more client data stores.Each client data store may contain tenant-specific data that is used aspart of providing a range of tenant-specific business and storageservices or functions, including but not limited to ERP, CRM, eCommerce,Human Resources management, payroll, storage services, etc. Data storesmay be implemented with any suitable data storage technology, includingstructured query language (SQL) based relational database managementsystems (RDBMS), file systems hosted by operating systems, objectstorage, etc.

In accordance with one embodiment of the invention, the distributedcomputing platform 602 may be a multi-tenant and service platformoperated by an entity in order to provide multiple tenants with a set ofbusiness related applications, data storage, and functionality. Theseapplications and functionality may include ones that a business uses tomanage various aspects of its operations. For example, the applicationsand functionality may include providing web-based access to businessinformation systems, thereby allowing a user with a browser and anInternet or intranet connection to view, enter, process, or modifycertain types of business information or any other type of information.

In an embodiment, the described methods and/or their equivalents may beimplemented with computer executable instructions. Thus, In anembodiment, a non-transitory computer readable/storage medium isconfigured with stored computer executable instructions of analgorithm/executable application that when executed by a machine(s)cause the machine(s) (and/or associated components) to perform themethod. Example machines include but are not limited to a processor, acomputer, a server operating in a cloud computing system, a serverconfigured in a Software as a Service (SaaS) architecture, a smartphone, and so on). In an embodiment, a computing device is implementedwith one or more executable algorithms that are configured to performany of the disclosed methods.

It will be appreciated that processes, architectures and/or proceduresdescribed herein can be implemented in hardware, firmware and/orsoftware. It will also be appreciated that the provisions set forthherein may apply to any type of special-purpose computer (e.g., filehost, storage server and/or storage serving appliance) and/orgeneral-purpose computer, including a standalone computer or portionthereof, embodied as or including a storage system. Moreover, theteachings herein can be configured to a variety of storage systemarchitectures including, but not limited to, a network-attached storageenvironment and/or a storage area network and disk assembly directlyattached to a client or host computer. Storage system should thereforebe taken broadly to include such arrangements in addition to anysubsystems configured to perform a storage function and associated withother equipment or systems.

In some embodiments, methods described and/or illustrated in thisdisclosure may be realized in whole or in part on computer-readablemedia. Computer readable media can include processor-executableinstructions configured to implement one or more of the methodspresented herein, and may include any mechanism for storing this datathat can be thereafter read by a computer system. Examples of computerreadable media include (hard) drives (e.g., accessible via networkattached storage (NAS)), Storage Area Networks (SAN), volatile andnon-volatile memory, such as read-only memory (ROM), random-accessmemory (RAM), electrically erasable programmable read-only memory(EEPROM) and/or flash memory, compact disk read only memory (CD-ROM)s,CD-Rs, compact disk re-writeable (CD-RW)s, DVDs, cassettes, magnetictape, magnetic disk storage, optical or non-optical data storage devicesand/or any other medium which can be used to store data.

Although the subject matter has been described in language specific tostructural features or methodological acts, it is to be understood thatthe subject matter defined in the appended claims is not necessarilylimited to the specific features or acts described above. Rather, thespecific features and acts described above are disclosed as exampleforms of implementing at least some of the claims.

Various operations of embodiments are provided herein. The order inwhich some or all of the operations are described should not beconstrued to imply that these operations are necessarily orderdependent. Alternative ordering will be appreciated given the benefit ofthis description. Further, it will be understood that not all operationsare necessarily present in each embodiment provided herein. Also, itwill be understood that not all operations are necessary in someembodiments.

Furthermore, the claimed subject matter is implemented as a method,apparatus, or article of manufacture using standard application orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer application accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

As used in this application, the terms “component”, “module,” “system”,“interface”, and the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentincludes a process running on a processor, a processor, an object, anexecutable, a thread of execution, an application, or a computer. By wayof illustration, both an application running on a controller and thecontroller can be a component. One or more components residing within aprocess or thread of execution and a component may be localized on onecomputer or distributed between two or more computers.

Moreover, “exemplary” is used herein to mean serving as an example,instance, illustration, etc., and not necessarily as advantageous. Asused in this application, “or” is intended to mean an inclusive “or”rather than an exclusive “or”. In addition, “a” and “an” as used in thisapplication are generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Also, at least one of A and B and/or the like generally means A orB and/or both A and B. Furthermore, to the extent that “includes”,“having”, “has”, “with”, or variants thereof are used, such terms areintended to be inclusive in a manner similar to the term “comprising”.

Many modifications may be made to the instant disclosure withoutdeparting from the scope or spirit of the claimed subject matter. Unlessspecified otherwise, “first,” “second,” or the like are not intended toimply a temporal aspect, a spatial aspect, an ordering, etc. Rather,such terms are merely used as identifiers, names, etc. for features,elements, items, etc. For example, a first set of information and asecond set of information generally correspond to set of information Aand set of information B or two different or two identical sets ofinformation or the same set of information.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

1-20. (canceled)
 21. A method comprising: caching data of writeoperations into memory; marking the data as dirty data to be stored fromthe memory to storage during a consistency point; and implementing theconsistency point by: storing the dirty data into data blocks of thestorage; assigning block numbers to the data blocks into which the dirtydata is stored; storing the block numbers into indirect blocks; andutilizing an encoding scheme to compact the indirect blocks into acompacted indirect block based upon patterns of the block numbers storedwithin the indirect blocks.
 22. The method of claim 21, wherein theindirect blocks comprise level (1) indirect blocks corresponding tointermediate nodes of a hierarchical tree structure, and whereinimplementing the consistency point comprises: storing the block numbersof the data blocks into the level (1) indirect blocks, wherein theencoding scheme is utilized to compact the level (1) indirect blocks inparallel with storing the block numbers of the data blocks into thelevel (1) indirect blocks.
 23. The method of claim 21, wherein theindirect blocks comprise level (1) indirect blocks corresponding tointermediate nodes of a hierarchical tree structure, and whereinimplementing the consistency point comprises: storing the block numbersof the data blocks into the level (1) indirect blocks, wherein theencoding scheme is utilized to compact the level (1) indirect blockssubsequent the block numbers of the data blocks being stored into thelevel (1) indirect blocks.
 24. The method of claim 21, wherein theutilizing the encoding scheme comprises: compacting the indirect blocksbased upon a sequential pattern of blocks numbers.
 25. The method ofclaim 21, wherein the utilizing the encoding scheme comprises: inresponse to identifying a repeating pattern of block numbers assigned tothe data blocks, compacting the indirect blocks based upon the repeatingpattern of blocks numbers.
 26. The method of claim 21, wherein theutilizing the encoding scheme comprises: identifying a base block numberof the block numbers assigned to the data blocks; identifying offsetsfrom the base block number of the blocks numbers assigned to the datablocks; and compacting the indirect blocks based upon the base blocknumber and the offsets.
 27. The method of claim 21, wherein theutilizing the encoding scheme comprises: for a set of block numbersencoded within the compacted indirect block, storing a base blocknumber, a count of subsequent block numbers after the base block number,and a pattern of the set of block numbers.
 28. The method of claim 21,wherein the utilizing the encoding scheme comprises: storing a tuplewithin the compacted indirect block to represent a set of block numbersassigned to one or more of the data blocks.
 29. The method of claim 21,wherein the utilizing the encoding scheme comprises: creating a firsttuple populated with a first base block number of a first set blocknumbers, a first count of additional sequential block numbers after thebase block number, and a sequential pattern identifier; creating asecond tuple populated with a second base block number of a second setblock numbers, a second count of additional sequential block numbersafter the second base block number, and a repeating pattern identifier;and storing the first tuple and the second tuple within the compactedindirect block.
 30. The method of claim 21, wherein the utilizing theencoding scheme comprises: creating a first tuple populated with a firstbase block number of a first set block numbers, a first count ofadditional sequential block numbers after the base block number, and asequential pattern identifier; creating a second tuple populated with asecond base block number of a second set block numbers, a second countof additional sequential block numbers after the base block number, anoffset pattern identifier, and offsets of the additional sequentialblock numbers from the second base block number; and storing the firsttuple and the second tuple within the compacted indirect block.
 31. Themethod of claim 21, wherein the utilizing the encoding scheme comprises:creating a first tuple populated with a first base block number of afirst set block numbers, a first count of additional sequential blocknumbers after the first base block number, and a repeating patternidentifier; and creating a second tuple populated with a second baseblock number of a second set block numbers, a second count of additionalsequential block numbers after the base block number, an offset patternidentifier, and offsets of the additional sequential block numbers fromthe second base block number; and storing the first tuple and the secondtuple within the compacted indirect block.
 32. The method of claim 21,wherein the utilizing the encoding scheme comprises: creating a firsttuple populated with a first base block number of a first set blocknumbers, a first count of additional sequential block numbers after thefirst base block number, and a repeating pattern identifier; creating asecond tuple populated with a second base block number of a second setblock numbers, a second count of additional sequential block numbersafter the base block number, an offset pattern identifier, and offsetsof the additional sequential block numbers from the second base blocknumber; creating a third tuple populated with a third base block numberof a third set block numbers, a third count of additional sequentialblock numbers after the base block number, and a sequential patternidentifier; and storing the first tuple, the second tuple, and the thirdtuple within the compacted indirect block.
 33. A system, comprising:storage within which data blocks of data are persisted; memory withinwhich indirect blocks used to locate the data blocks are stored; a meansfor receiving a request to access a data block within an object; a meansfor uncompacting a compacted indirect block to identify an indirectblock associated with the data block; and a means for utilizing a blocknumber within the indirect block to read the data block from storage.34. The system of claim 33, wherein the means for receiving the requestis a processor.
 35. The system of claim 33, wherein the means foruncompacting the compacted indirect block is a compaction processexecuted by a processor.
 36. The system of claim 33, wherein the storageis a data storage device, and wherein the means for utilizing the blocknumber within the indirect block to read the data block from storage isa disk module.
 37. The system of claim 33, comprising: a means forcreating a first tuple populated with a first base block number of afirst set block numbers, a first count of additional sequential blocknumbers after the base block number, and a sequential patternidentifier; a means for creating a second tuple populated with a secondbase block number of a second set block numbers, a second count ofadditional sequential block numbers after the second base block number,and a repeating pattern identifier; and a means for storing the firsttuple and the second tuple within the compacted indirect block.
 38. Thesystem of claim 33, comprising: a means for creating a first tuplepopulated with a first base block number of a first set block numbers, afirst count of additional sequential block numbers after the base blocknumber, and a sequential pattern identifier; a means for creating asecond tuple populated with a second base block number of a second setblock numbers, a second count of additional sequential block numbersafter the base block number, an offset pattern identifier, and offsetsof the additional sequential block numbers from the second base blocknumber; and a means for storing the first tuple and the second tuplewithin the compacted indirect block.
 39. The system of claim 33,comprising: a means for creating a first tuple populated with a firstbase block number of a first set block numbers, a first count ofadditional sequential block numbers after the first base block number,and a repeating pattern identifier; and a means for creating a secondtuple populated with a second base block number of a second set blocknumbers, a second count of additional sequential block numbers after thebase block number, an offset pattern identifier, and offsets of theadditional sequential block numbers from the second base block number;and a means for storing the first tuple and the second tuple within thecompacted indirect block.
 40. A non-transitory machine readable mediumcomprising instructions for performing a method, which when executed bya machine, causes the machine to: representing a volume as a structurecomprising data blocks within which data of the volume is stored,wherein the volume is associated with a set of metadata corresponding toat least one of a size of the volume, a modification date of a filewithin the volume, a creation time of the file, or a state of areplication relationship of the volume; compacting the set of metadatainto compacted metadata; and storing the compacted metadata into memoryfor managing the volume.